Research is at the core of scientific inquiry. Science of Statistics has a broad range of applications in research such as health, medicine, finance, psychology, etc. Mentoring students in research in the course of their education gives them opportunities to critically examine and affirm their commitment to their future career. Mentoring undergraduate researchers has additional benefits. It can help senior mentors educate new researchers and create more inclusive disciplines while advancing their own science in partnership with smart, enthusiastic, passionate, and hard-working students. It also provides junior mentors with opportunities to develop professional skills in advising and teaching. Both these forms of teaching and mentoring measure success by enhancements in understanding of complex topics and critical thinking skills. Each mentor has a different approach and uses different methods in working with their students, but there are common approaches and practices that mentors can use to contribute to the success of every student researcher. In this workshop, we facilitate activities drawn from best practices in Statistics education by utilizing the work by Aaron M. Elllison and Manisha V. Patel: Success in Mentoring Your Student Researchers, Moving STEMM Forward, as well as sharing our own practical ideas for involving and mentoring students in research. 

Biographies:

Omidali Aghababaei Jazi is an Assistant Professor, Teaching Stream, in the Department of Mathematical and Computational Sciences at the University of Toronto Mississauga (UTM). He has taught a variety of courses including Probability and Statistics, Stochastic Processes, and Experimental Design, supervised undergraduate students for their research projects, and facilitated SSC sessions and the case study competition over the past years. His research interests are Statistics education, analysis of biased survival data, and analysis of longitudinal data with informative follow-up.

Diana Skrzydlo is an Associate Professor, Teaching Stream in the Department of Statistics and Actuarial Science and the current Math Faculty Teaching Fellow. She has been teaching at the University of Waterloo since 2007 and has spoken widely on innovative teaching and assessment techniques, including in Indonesia with the READI project. She has a BMath (2006) and MMath (2007) from UW, and achieved her ASA designation from the Society of Actuaries in 2018.

Lijia Wang is an Assistant Professor, Teaching Stream (LTA), in the Department of Statistical Sciences at the University of Toronto. He has taught Statistics courses including Probability and Statistics. His passion is Statistical education, and his research interest includes causal inference, causal mediation analysis with application in designing novel statistical models for biomedical data. 

James McVittie is an Assistant Professor in the Department of Mathematics and Statistics at the University of Regina. He has taught statistics courses at all levels of undergraduate studies and has supervised students at both the undergraduate and graduate levels. His research focuses primarily on survival analysis as well as problems related to missing data.